2 code implementations • 2 Aug 2023 • Fenghe Tang, Jianrui Ding, Lingtao Wang, Chunping Ning, S. Kevin Zhou
In order to extract global context information while taking advantage of the inductive bias, we propose CMUNeXt, an efficient fully convolutional lightweight medical image segmentation network, which enables fast and accurate auxiliary diagnosis in real scene scenarios.
1 code implementation • 24 May 2023 • Lingtao Wang, Jianrui Ding, Fenghe Tang, Chunping Ning
Accurate detection of thyroid lesions is a critical aspect of computer-aided diagnosis.
1 code implementation • 16 May 2023 • Fenghe Tang, Jianrui Ding, Lingtao Wang, Min Xian, Chunping Ning
Our approach enables the effective transfer of probability distribution knowledge to the segmentation network, resulting in improved segmentation accuracy.
2 code implementations • 24 Oct 2022 • Fenghe Tang, Lingtao Wang, Chunping Ning, Min Xian, Jianrui Ding
However, due to the inherent local characteristics of ordinary convolution operations, U-Net encoder cannot effectively extract global context information.